Description
Kernel Density Estimation. Nadaraya Watson Kernel Regression. Stochastic Simulation. Inverse Transform Sampling. Rejection Method. Variance Reduction. Importance Sampling. Resampling Methods: Bootstrap and Jackknife. Cross-Validation. Stochastic Optimization: Genetic Algorithm, Simulated Annealing, Tabu Search. EM Algorithm. Variable Selection. Shrinkage Methods: Ridge and Lasso.
Professors
Semester
Spring Semester
Category
Obligatory
Lecture Hours
3 hours
Credits
5